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<h1><a href="aiplatform_v1beta1.html">Vertex AI API</a> . <a href="aiplatform_v1beta1.projects.html">projects</a> . <a href="aiplatform_v1beta1.projects.locations.html">locations</a> . <a href="aiplatform_v1beta1.projects.locations.notebookExecutionJobs.html">notebookExecutionJobs</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
  <code><a href="aiplatform_v1beta1.projects.locations.notebookExecutionJobs.operations.html">operations()</a></code>
</p>
<p class="firstline">Returns the operations Resource.</p>

<p class="toc_element">
  <code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
  <code><a href="#create">create(parent, body=None, notebookExecutionJobId=None, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a NotebookExecutionJob.</p>
<p class="toc_element">
  <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes a NotebookExecutionJob.</p>
<p class="toc_element">
  <code><a href="#generateAccessToken">generateAccessToken(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Internal only: Called from Compute Engine instance to obtain EUC for owner Anonymous access: authenticates caller using VM identity JWT. Design doc: go/colab-on-vertex-euc-dd</p>
<p class="toc_element">
  <code><a href="#get">get(name, view=None, x__xgafv=None)</a></code></p>
<p class="firstline">Gets a NotebookExecutionJob.</p>
<p class="toc_element">
  <code><a href="#list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, view=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists NotebookExecutionJobs in a Location.</p>
<p class="toc_element">
  <code><a href="#list_next">list_next()</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<p class="toc_element">
  <code><a href="#reportEvent">reportEvent(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline"></p>
<h3>Method Details</h3>
<div class="method">
    <code class="details" id="close">close()</code>
  <pre>Close httplib2 connections.</pre>
</div>

<div class="method">
    <code class="details" id="create">create(parent, body=None, notebookExecutionJobId=None, x__xgafv=None)</code>
  <pre>Creates a NotebookExecutionJob.

Args:
  parent: string, Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}` (required)
  body: object, The request body.
    The object takes the form of:

{ # NotebookExecutionJob represents an instance of a notebook execution.
  &quot;createTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this NotebookExecutionJob was created.
  &quot;customEnvironmentSpec&quot;: { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
    &quot;machineSpec&quot;: { # Specification of a single machine. # The specification of a single machine for the execution job.
      &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
      &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
      &quot;gpuPartitionSize&quot;: &quot;A String&quot;, # Optional. Immutable. The Nvidia GPU partition size. When specified, the requested accelerators will be partitioned into smaller GPU partitions. For example, if the request is for 8 units of NVIDIA A100 GPUs, and gpu_partition_size=&quot;1g.10gb&quot;, the service will create 8 * 7 = 56 partitioned MIG instances. The partition size must be a value supported by the requested accelerator. Refer to [Nvidia GPU Partitioning](https://cloud.google.com/kubernetes-engine/docs/how-to/gpus-multi#multi-instance_gpu_partitions) for the available partition sizes. If set, the accelerator_count should be set to 1.
      &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
      &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
      &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
        &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
        &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
        &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation or reservation block.
          &quot;A String&quot;,
        ],
      },
      &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
    },
    &quot;networkSpec&quot;: { # Network spec. # The network configuration to use for the execution job.
      &quot;enableInternetAccess&quot;: True or False, # Whether to enable public internet access. Default false.
      &quot;network&quot;: &quot;A String&quot;, # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
      &quot;subnetwork&quot;: &quot;A String&quot;, # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
    },
    &quot;persistentDiskSpec&quot;: { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
      &quot;diskSizeGb&quot;: &quot;A String&quot;, # Size in GB of the disk (default is 100GB).
      &quot;diskType&quot;: &quot;A String&quot;, # Type of the disk (default is &quot;pd-standard&quot;). Valid values: &quot;pd-ssd&quot; (Persistent Disk Solid State Drive) &quot;pd-standard&quot; (Persistent Disk Hard Disk Drive) &quot;pd-balanced&quot; (Balanced Persistent Disk) &quot;pd-extreme&quot; (Extreme Persistent Disk)
    },
  },
  &quot;dataformRepositorySource&quot;: { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
    &quot;commitSha&quot;: &quot;A String&quot;, # The commit SHA to read repository with. If unset, the file will be read at HEAD.
    &quot;dataformRepositoryResourceName&quot;: &quot;A String&quot;, # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
  },
  &quot;directNotebookSource&quot;: { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
    &quot;content&quot;: &quot;A String&quot;, # The base64-encoded contents of the input notebook file.
  },
  &quot;displayName&quot;: &quot;A String&quot;, # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
  &quot;encryptionSpec&quot;: { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookRuntimeTemplate has an encryption spec.
    &quot;kmsKeyName&quot;: &quot;A String&quot;, # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
  },
  &quot;executionTimeout&quot;: &quot;A String&quot;, # Max running time of the execution job in seconds (default 86400s / 24 hrs).
  &quot;executionUser&quot;: &quot;A String&quot;, # The user email to run the execution as. Only supported by Colab runtimes.
  &quot;gcsNotebookSource&quot;: { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
    &quot;generation&quot;: &quot;A String&quot;, # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
    &quot;uri&quot;: &quot;A String&quot;, # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
  },
  &quot;gcsOutputUri&quot;: &quot;A String&quot;, # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
  &quot;jobState&quot;: &quot;A String&quot;, # Output only. The state of the NotebookExecutionJob.
  &quot;kernelName&quot;: &quot;A String&quot;, # The name of the kernel to use during notebook execution. If unset, the default kernel is used.
  &quot;labels&quot;: { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with &quot;aiplatform.googleapis.com/&quot; and are immutable.
    &quot;a_key&quot;: &quot;A String&quot;,
  },
  &quot;name&quot;: &quot;A String&quot;, # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
  &quot;notebookRuntimeTemplateResourceName&quot;: &quot;A String&quot;, # The NotebookRuntimeTemplate to source compute configuration from.
  &quot;scheduleResourceName&quot;: &quot;A String&quot;, # The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
  &quot;serviceAccount&quot;: &quot;A String&quot;, # The service account to run the execution as.
  &quot;status&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  &quot;updateTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
  &quot;workbenchRuntime&quot;: { # Configuration for a Workbench Instances-based environment. # The Workbench runtime configuration to use for the notebook execution.
  },
}

  notebookExecutionJobId: string, Optional. User specified ID for the NotebookExecutionJob.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # This resource represents a long-running operation that is the result of a network API call.
  &quot;done&quot;: True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
  &quot;error&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  &quot;metadata&quot;: { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
    &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
  },
  &quot;name&quot;: &quot;A String&quot;, # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
  &quot;response&quot;: { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
    &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
  },
}</pre>
</div>

<div class="method">
    <code class="details" id="delete">delete(name, x__xgafv=None)</code>
  <pre>Deletes a NotebookExecutionJob.

Args:
  name: string, Required. The name of the NotebookExecutionJob resource to be deleted. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # This resource represents a long-running operation that is the result of a network API call.
  &quot;done&quot;: True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
  &quot;error&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  &quot;metadata&quot;: { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
    &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
  },
  &quot;name&quot;: &quot;A String&quot;, # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
  &quot;response&quot;: { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
    &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
  },
}</pre>
</div>

<div class="method">
    <code class="details" id="generateAccessToken">generateAccessToken(name, body=None, x__xgafv=None)</code>
  <pre>Internal only: Called from Compute Engine instance to obtain EUC for owner Anonymous access: authenticates caller using VM identity JWT. Design doc: go/colab-on-vertex-euc-dd

Args:
  name: string, Required. The name of the resource requesting the OAuth2 token. Format: `projects/{project}/locations/{location}/notebookRuntimes/{notebook_runtime}` `projects/{project}/locations/{location}/notebookExecutionJobs/{notebook_execution_job}` (required)
  body: object, The request body.
    The object takes the form of:

{ # Request message for NotebookInternalService.GenerateAccessToken.
  &quot;vmToken&quot;: &quot;A String&quot;, # Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance-identity
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response message for NotebookInternalService.GenerateToken.
  &quot;accessToken&quot;: &quot;A String&quot;, # Short-lived access token string which may be used to access Google APIs.
  &quot;expiresIn&quot;: 42, # The time in seconds when the access token expires. Typically that&#x27;s 3600.
  &quot;scope&quot;: &quot;A String&quot;, # Space-separated list of scopes contained in the returned token. https://cloud.google.com/docs/authentication/token-types#access-contents
  &quot;tokenType&quot;: &quot;A String&quot;, # Type of the returned access token (e.g. &quot;Bearer&quot;). It specifies how the token must be used. Bearer tokens may be used by any entity without proof of identity.
}</pre>
</div>

<div class="method">
    <code class="details" id="get">get(name, view=None, x__xgafv=None)</code>
  <pre>Gets a NotebookExecutionJob.

Args:
  name: string, Required. The name of the NotebookExecutionJob resource. (required)
  view: string, Optional. The NotebookExecutionJob view. Defaults to BASIC.
    Allowed values
      NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED - When unspecified, the API defaults to the BASIC view.
      NOTEBOOK_EXECUTION_JOB_VIEW_BASIC - Includes all fields except for direct notebook inputs.
      NOTEBOOK_EXECUTION_JOB_VIEW_FULL - Includes all fields.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # NotebookExecutionJob represents an instance of a notebook execution.
  &quot;createTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this NotebookExecutionJob was created.
  &quot;customEnvironmentSpec&quot;: { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
    &quot;machineSpec&quot;: { # Specification of a single machine. # The specification of a single machine for the execution job.
      &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
      &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
      &quot;gpuPartitionSize&quot;: &quot;A String&quot;, # Optional. Immutable. The Nvidia GPU partition size. When specified, the requested accelerators will be partitioned into smaller GPU partitions. For example, if the request is for 8 units of NVIDIA A100 GPUs, and gpu_partition_size=&quot;1g.10gb&quot;, the service will create 8 * 7 = 56 partitioned MIG instances. The partition size must be a value supported by the requested accelerator. Refer to [Nvidia GPU Partitioning](https://cloud.google.com/kubernetes-engine/docs/how-to/gpus-multi#multi-instance_gpu_partitions) for the available partition sizes. If set, the accelerator_count should be set to 1.
      &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
      &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
      &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
        &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
        &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
        &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation or reservation block.
          &quot;A String&quot;,
        ],
      },
      &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
    },
    &quot;networkSpec&quot;: { # Network spec. # The network configuration to use for the execution job.
      &quot;enableInternetAccess&quot;: True or False, # Whether to enable public internet access. Default false.
      &quot;network&quot;: &quot;A String&quot;, # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
      &quot;subnetwork&quot;: &quot;A String&quot;, # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
    },
    &quot;persistentDiskSpec&quot;: { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
      &quot;diskSizeGb&quot;: &quot;A String&quot;, # Size in GB of the disk (default is 100GB).
      &quot;diskType&quot;: &quot;A String&quot;, # Type of the disk (default is &quot;pd-standard&quot;). Valid values: &quot;pd-ssd&quot; (Persistent Disk Solid State Drive) &quot;pd-standard&quot; (Persistent Disk Hard Disk Drive) &quot;pd-balanced&quot; (Balanced Persistent Disk) &quot;pd-extreme&quot; (Extreme Persistent Disk)
    },
  },
  &quot;dataformRepositorySource&quot;: { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
    &quot;commitSha&quot;: &quot;A String&quot;, # The commit SHA to read repository with. If unset, the file will be read at HEAD.
    &quot;dataformRepositoryResourceName&quot;: &quot;A String&quot;, # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
  },
  &quot;directNotebookSource&quot;: { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
    &quot;content&quot;: &quot;A String&quot;, # The base64-encoded contents of the input notebook file.
  },
  &quot;displayName&quot;: &quot;A String&quot;, # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
  &quot;encryptionSpec&quot;: { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookRuntimeTemplate has an encryption spec.
    &quot;kmsKeyName&quot;: &quot;A String&quot;, # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
  },
  &quot;executionTimeout&quot;: &quot;A String&quot;, # Max running time of the execution job in seconds (default 86400s / 24 hrs).
  &quot;executionUser&quot;: &quot;A String&quot;, # The user email to run the execution as. Only supported by Colab runtimes.
  &quot;gcsNotebookSource&quot;: { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
    &quot;generation&quot;: &quot;A String&quot;, # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
    &quot;uri&quot;: &quot;A String&quot;, # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
  },
  &quot;gcsOutputUri&quot;: &quot;A String&quot;, # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
  &quot;jobState&quot;: &quot;A String&quot;, # Output only. The state of the NotebookExecutionJob.
  &quot;kernelName&quot;: &quot;A String&quot;, # The name of the kernel to use during notebook execution. If unset, the default kernel is used.
  &quot;labels&quot;: { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with &quot;aiplatform.googleapis.com/&quot; and are immutable.
    &quot;a_key&quot;: &quot;A String&quot;,
  },
  &quot;name&quot;: &quot;A String&quot;, # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
  &quot;notebookRuntimeTemplateResourceName&quot;: &quot;A String&quot;, # The NotebookRuntimeTemplate to source compute configuration from.
  &quot;scheduleResourceName&quot;: &quot;A String&quot;, # The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
  &quot;serviceAccount&quot;: &quot;A String&quot;, # The service account to run the execution as.
  &quot;status&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  &quot;updateTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
  &quot;workbenchRuntime&quot;: { # Configuration for a Workbench Instances-based environment. # The Workbench runtime configuration to use for the notebook execution.
  },
}</pre>
</div>

<div class="method">
    <code class="details" id="list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, view=None, x__xgafv=None)</code>
  <pre>Lists NotebookExecutionJobs in a Location.

Args:
  parent: string, Required. The resource name of the Location from which to list the NotebookExecutionJobs. Format: `projects/{project}/locations/{location}` (required)
  filter: string, Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookExecutionJob` supports = and !=. `notebookExecutionJob` represents the NotebookExecutionJob ID. * `displayName` supports = and != and regex. * `schedule` supports = and != and regex. Some examples: * `notebookExecutionJob=&quot;123&quot;` * `notebookExecutionJob=&quot;my-execution-job&quot;` * `displayName=&quot;myDisplayName&quot;` and `displayName=~&quot;myDisplayNameRegex&quot;`
  orderBy: string, Optional. A comma-separated list of fields to order by, sorted in ascending order. Use &quot;desc&quot; after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`.
  pageSize: integer, Optional. The standard list page size.
  pageToken: string, Optional. The standard list page token. Typically obtained via ListNotebookExecutionJobsResponse.next_page_token of the previous NotebookService.ListNotebookExecutionJobs call.
  view: string, Optional. The NotebookExecutionJob view. Defaults to BASIC.
    Allowed values
      NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED - When unspecified, the API defaults to the BASIC view.
      NOTEBOOK_EXECUTION_JOB_VIEW_BASIC - Includes all fields except for direct notebook inputs.
      NOTEBOOK_EXECUTION_JOB_VIEW_FULL - Includes all fields.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response message for [NotebookService.CreateNotebookExecutionJob]
  &quot;nextPageToken&quot;: &quot;A String&quot;, # A token to retrieve next page of results. Pass to ListNotebookExecutionJobsRequest.page_token to obtain that page.
  &quot;notebookExecutionJobs&quot;: [ # List of NotebookExecutionJobs in the requested page.
    { # NotebookExecutionJob represents an instance of a notebook execution.
      &quot;createTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this NotebookExecutionJob was created.
      &quot;customEnvironmentSpec&quot;: { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
        &quot;machineSpec&quot;: { # Specification of a single machine. # The specification of a single machine for the execution job.
          &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
          &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
          &quot;gpuPartitionSize&quot;: &quot;A String&quot;, # Optional. Immutable. The Nvidia GPU partition size. When specified, the requested accelerators will be partitioned into smaller GPU partitions. For example, if the request is for 8 units of NVIDIA A100 GPUs, and gpu_partition_size=&quot;1g.10gb&quot;, the service will create 8 * 7 = 56 partitioned MIG instances. The partition size must be a value supported by the requested accelerator. Refer to [Nvidia GPU Partitioning](https://cloud.google.com/kubernetes-engine/docs/how-to/gpus-multi#multi-instance_gpu_partitions) for the available partition sizes. If set, the accelerator_count should be set to 1.
          &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
          &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
          &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
            &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
            &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
            &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation or reservation block.
              &quot;A String&quot;,
            ],
          },
          &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
        },
        &quot;networkSpec&quot;: { # Network spec. # The network configuration to use for the execution job.
          &quot;enableInternetAccess&quot;: True or False, # Whether to enable public internet access. Default false.
          &quot;network&quot;: &quot;A String&quot;, # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
          &quot;subnetwork&quot;: &quot;A String&quot;, # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
        },
        &quot;persistentDiskSpec&quot;: { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
          &quot;diskSizeGb&quot;: &quot;A String&quot;, # Size in GB of the disk (default is 100GB).
          &quot;diskType&quot;: &quot;A String&quot;, # Type of the disk (default is &quot;pd-standard&quot;). Valid values: &quot;pd-ssd&quot; (Persistent Disk Solid State Drive) &quot;pd-standard&quot; (Persistent Disk Hard Disk Drive) &quot;pd-balanced&quot; (Balanced Persistent Disk) &quot;pd-extreme&quot; (Extreme Persistent Disk)
        },
      },
      &quot;dataformRepositorySource&quot;: { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
        &quot;commitSha&quot;: &quot;A String&quot;, # The commit SHA to read repository with. If unset, the file will be read at HEAD.
        &quot;dataformRepositoryResourceName&quot;: &quot;A String&quot;, # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
      },
      &quot;directNotebookSource&quot;: { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
        &quot;content&quot;: &quot;A String&quot;, # The base64-encoded contents of the input notebook file.
      },
      &quot;displayName&quot;: &quot;A String&quot;, # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
      &quot;encryptionSpec&quot;: { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookRuntimeTemplate has an encryption spec.
        &quot;kmsKeyName&quot;: &quot;A String&quot;, # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
      },
      &quot;executionTimeout&quot;: &quot;A String&quot;, # Max running time of the execution job in seconds (default 86400s / 24 hrs).
      &quot;executionUser&quot;: &quot;A String&quot;, # The user email to run the execution as. Only supported by Colab runtimes.
      &quot;gcsNotebookSource&quot;: { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
        &quot;generation&quot;: &quot;A String&quot;, # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
        &quot;uri&quot;: &quot;A String&quot;, # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
      },
      &quot;gcsOutputUri&quot;: &quot;A String&quot;, # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
      &quot;jobState&quot;: &quot;A String&quot;, # Output only. The state of the NotebookExecutionJob.
      &quot;kernelName&quot;: &quot;A String&quot;, # The name of the kernel to use during notebook execution. If unset, the default kernel is used.
      &quot;labels&quot;: { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with &quot;aiplatform.googleapis.com/&quot; and are immutable.
        &quot;a_key&quot;: &quot;A String&quot;,
      },
      &quot;name&quot;: &quot;A String&quot;, # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
      &quot;notebookRuntimeTemplateResourceName&quot;: &quot;A String&quot;, # The NotebookRuntimeTemplate to source compute configuration from.
      &quot;scheduleResourceName&quot;: &quot;A String&quot;, # The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
      &quot;serviceAccount&quot;: &quot;A String&quot;, # The service account to run the execution as.
      &quot;status&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
        &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
        &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
          {
            &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
          },
        ],
        &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
      },
      &quot;updateTime&quot;: &quot;A String&quot;, # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
      &quot;workbenchRuntime&quot;: { # Configuration for a Workbench Instances-based environment. # The Workbench runtime configuration to use for the notebook execution.
      },
    },
  ],
}</pre>
</div>

<div class="method">
    <code class="details" id="list_next">list_next()</code>
  <pre>Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call &#x27;execute()&#x27; on to request the next
          page. Returns None if there are no more items in the collection.
        </pre>
</div>

<div class="method">
    <code class="details" id="reportEvent">reportEvent(name, body=None, x__xgafv=None)</code>
  <pre>

Args:
  name: string, Required. The name of the NotebookExecutionJob resource. Format: `projects/{project}/locations/{location}/notebookExecutionJobs/{notebook_execution_jobs}` (required)
  body: object, The request body.
    The object takes the form of:

{ # Request message for NotebookInternalService.ReportExecutionEvent.
  &quot;eventType&quot;: &quot;A String&quot;, # Required. The type of the event.
  &quot;status&quot;: { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Optional. The error details of the event.
    &quot;code&quot;: 42, # The status code, which should be an enum value of google.rpc.Code.
    &quot;details&quot;: [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        &quot;a_key&quot;: &quot;&quot;, # Properties of the object. Contains field @type with type URL.
      },
    ],
    &quot;message&quot;: &quot;A String&quot;, # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  &quot;vmToken&quot;: &quot;A String&quot;, # Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance-identity
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response message for NotebookInternalService.ReportExecutionEvent.
}</pre>
</div>

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